Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP).

Risk assessment and risk prediction have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP).

Risk assessment and risk prediction have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

Risk prediction tools in cardiovascular disease prevention: A report from the ESC Prevention of CVD Programme led by the European Association of Preventive Cardiology (EAPC) in collaboration with the Acute Cardiovascular Care Association (ACCA) and the Association of Cardiovascular Nursing and Allied Professions (ACNAP).

Risk assessment have become essential in the prevention of cardiovascular disease. Even though risk prediction tools are recommended in the European guidelines, they are not adequately implemented in clinical practice. Risk prediction tools are meant to estimate prognosis in an unbiased and reliable way and to provide objective information on outcome probabilities. They support informed treatment decisions about the initiation or adjustment of preventive medication. Risk prediction tools facilitate risk communication to the patient and their family, and this may increase commitment and motivation to improve their health. Over the years many risk algorithms have been developed to predict 10-year cardiovascular mortality or lifetime risk in different populations, such as in healthy individuals, patients with established cardiovascular disease and patients with diabetes mellitus. Each risk algorithm has its own limitations, so different algorithms should be used in different patient populations. Risk algorithms are made available for use in clinical practice by means of - usually interactive and online available - tools. To help the clinician to choose the right tool for the right patient, a summary of available tools is provided. When choosing a tool, physicians should consider medical history, geographical region, clinical guidelines and additional risk measures among other things. Currently, the U-prevent.com website is the only risk prediction tool providing prediction algorithms for all patient categories, and its implementation in clinical practice is suggested/advised by the European Association of Preventive Cardiology.

A new selection method to increase the health benefits of CVD prevention strategies.

Background Cardiovascular disease (CVD) prevention is commonly focused on providing individuals at high predicted CVD risk with preventive medication. Whereas CVD risk increases rapidly with age, current risk-based selection of individuals mainly targets the elderly. However, the lifelong (preventable) consequences of CVD events may be larger in younger individuals. The purpose of this paper is to investigate if health benefits from preventive treatment may increase when the selection strategy is further optimised. Methods Data from three Dutch cohorts were combined ( n = 47469, men:women 1:1.92) and classified into subgroups based on age and gender. The Framingham global risk score was used to estimate 10-year CVD risk. The associated lifelong burden of CVD events according to this 10-year CVD risk was expressed as quality-adjusted life years lost. Based on this approach, the additional health benefits from preventive treatment, reducing this 10-year CVD risk, from selecting individuals based on their expected CVD burden rather than their expected CVD risk were estimated. These benefits were expressed as quality-adjusted life years gained over lifetime. Results When using the current selection strategy (10% risk threshold), 32% of the individuals were selected for preventive treatment. When the same proportion was selected based on burden, more younger and fewer older individuals would receive treatment. Across all individuals, the gain in quality-adjusted life years was 217 between the two strategies, over a 10-year time horizon. In addition, when combining the strategies 5% extra eligible individuals were selected resulting in a gain of 628 quality-adjusted life years. Conclusion Improvement of the selection approach of individuals can help to reduce further the CVD burden. Selecting individuals for preventive treatment based on their expected CVD burden will provide more younger and fewer older individuals with treatment, and will reduce the overall CVD burden.

SPRINT trial: It's not just the blood pressure!

Background The SPRINT trial showed a beneficial effect of systolic blood pressure treatment targets of 120 mmHg on cardiovascular risk compared to targets of 140 mmHg. However, differences in medication use, most importantly diuretics, are suggested as an alternative explanation. This post-hoc analysis aimed to determine whether the reduced event rate can be attributed to changes in systolic blood pressure (ΔSBP) . Methods Analyses were based on all 9361 participants of the SPRINT trial. ΔSBP was defined as the change between baseline and 6-month follow-up systolic blood pressure. Major cardiovascular events were myocardial infarction, other acute coronary syndromes, stroke, heart failure, or cardiovascular death. Cox regression was used to describe the relation between ΔSBP and major cardiovascular events. Analyses were performed separately for patients in the lowest tertile of baseline systolic blood pressure, as the SPRINT trial reported the highest treatment effect in this subgroup. Results The relation between ΔSBP and major cardiovascular events was a hazard ratio per 10 mmHg decrease of 0.93 (95% confidence interval 0.89-0.98). Similar results were found within the lowest tertile of baseline systolic blood pressure: hazard ratio per 10 mmHg decrease 0.91 (95% confidence interval 0.82-1.01). Conclusion Our results show that lowering blood pressure prevents cardiovascular disease. However, not all the positive effects in the SPRINT trial could be explained by ΔSBP. Alternative explanations, such as differences in medication use, should be considered for the positive findings of the SPRINT trial.